Mobile communications devices have become an integral part of society over the last two decades. Indeed, more than eighty-two percent of Americans own a mobile communications device, for example, a cell phone. The typical mobile communications device includes an antenna, and a transceiver coupled to the antenna. The transceiver and the antenna cooperate to transmit and receive communications signals.
Before transmission, the typical mobile communications device modulates digital data onto an analog signal. As will be readily appreciated by the skilled person, there is a plurality of modulations available for most applications. Some particularly advantageous modulations include, for example, continuous phase modulation (CPM). The constant envelope characteristics of this modulation provide for lower energy demands on the power amplifier of mobile communications devices, for example, by reducing the peak-to-average power ratio (PAPR), increasing average transmit power (providing greater transmission range), and increasing amplifier efficiency, i.e. allowing the use of non-linear amplifiers such as Class C amplifiers. Moreover, CPM provides for efficient use of available bandwidth.
A potential drawback of CPM modulations is the use of the inherent memory of the modulation when demodulating/decoding the waveform in order to obtain good demodulator performance. When the mobile communications device receives a transmitted signal which uses a modulation with memory, the decoder uses not only the current signal portion to demodulate but in addition uses information from previous signal portions, i.e. memory, to demodulate the current signal. In other words, the phase of the transmitted signal is dependent on previous signaling intervals.
Decoding modulations with memory increases the computational and memory demands on the transceiver, i.e. a maximum likelihood sequence estimator (MLSE) or the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm is typically used to demodulate modulations with memory, thereby increasing the complexity of the device, which may be undesirable in a limited power compact mobile device. More so, when the received signal has a multipath component to it, the size of the MLSE or BCJR trellis structure used to demodulate the signal grows exponentially, which may make practical implementation in a mobile communications device difficult since computational resources are limited.
In typical mobile communications devices that use multiple different bandwidth efficient modulations, such as various CPM waveforms (concatenated with convolutional forward error correction (FEC) codes), the demodulation and multipath MLSE or BCJR trellis may require a large amount of computational resources to implement the decoders for all possible combinations of modulation and FEC or yield very slow programmable decoders which can be used for all waveforms. In particular, the trellis structure maps may become large and onerous in computational overhead. One approach is to reuse trellis elements for different applications, for example, as disclosed in U.S. Pat. No. 7,020,827 to Gatherer et al., which discloses reusing state metrics to provide multiple trellis structures coupled in cascade.
Another approach is to reuse elements of one trellis structure (intended for one modulation) for another trellis structure (intended for another different modulation). This approach typically uses multiplexers to route and reroute inputs and outputs throughout the trellis structure. A drawback to this approach is the multiplexers may also consume a large amount of computational resources and add to decoder complexity.